Scientific Advances in STEM: From Professor to Students

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Topic Information

Dear Colleagues, 

The aim of this article collection is to contribute to the advancement of the Science and Engineering fields and their impact on the industrial sector, which requires a multidisciplinary approach.

The University generates and transmits knowledge to serve society. Social demands continuously evolve, mainly as a consequence of cultural, scientific, and technological development. Researchers must contextualize the subjects they investigate to their application to the local industry and community organizations, frequently using a multidisciplinary point of view, to enhance the progress in a wide variety of fields (aeronautics, automotive, biomedical, electrical and renewable energy, communications, environmental, electronic components, etc.).

Most investigations in the fields of science and engineering require the work of multidisciplinary teams, representing a stockpile of research projects in different stages (final year projects, master’s or doctoral studies). In this context, this Topic offers a framework for integrating interdisciplinary research, drawing together experimental and theoretical contributions in a wide variety of fields. Topics of interest could include, but are not limited to:

General topics:

• Science and technology of materials;
• Physics and applied mathematics;
• Industrial and environmental chemistry;
• Analytic chemistry;
• Intelligent systems and electronic technology;
• Product design, development, and engineering;
• Computerized, robotic, and neuromorphic industrial systems;
• Computer architecture and technology.

Particular Themes:

• Coatings and nanostructured materials for solar energy applications (in particular for high-temperature concentrated solar power applications);
• Development of functional materials for additive manufacturing (i.e., applications in biomedicine);
• Advanced optical characterization or nano- and microstructures and thin films;
• Biopolymer-based superabsorbent materials from agro-food bioresidues;
• Biodegradable protein‐based polymer materials for the controlled release of micronutrients in horticulture;
• Interfacial rheology and its applications to protein-based emulsion processing and stability;
• Deep-learning systems for diagnosis, prevention, and pattern recognition;
• Bio-inspired systems for sensory fusion and control;
• Current advances in computer architecture;
• Artificial intelligence in smart cities applications;
• Energy forecasting and flexibility services;
• Advances in food and by-products development and characterization;
• New trends in sustainable cities and industries;
• Intelligent and sustainable optimization of industrial engineering projects;
• Multifunctional and smart toys for children with autism spectrum disorder;
• Weighting with life-cycle assessment and cradle-to-cradle (methodology for global sustainability design social and socio-economic life cycle assessment: towards quantitative methods in small and medium-sized enterprises);
• Work of separation in metal–metal interfaces;
• Emerging pollutants in the urban water cycle;
• Analysis of emerging pollutants in environmental samples;
• Design, manufacture, and characterization of WC-Co/WC-Co laminates;
• Wear and scratch resistance of porous materials for biomedical applications;
• Biomechanical and biofunctional behavior of porous titanium parts coated with hydroxyapatite using the sol–gel technique;
• Bioactive glass bilayer coatings on porous titanium samples.

Prof. Dr. Yadir Torres Hernández
Dr. Manuel Félix Ángel
Dr. Ana María Beltrán Custodio
Prof. Dr. Francisco Garcia Moreno

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Metals metals	2.5	5.3	2011	18 Days	CHF 2600
Polymers polymers	4.9	9.7	2009	14 Days	CHF 2700
Foods foods	5.1	8.7	2012	14.9 Days	CHF 2900
Sustainability sustainability	3.3	7.7	2009	19.3 Days	CHF 2400
Sensors sensors	3.5	8.2	2001	19.7 Days	CHF 2600

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Published Papers (20 papers)

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14 pages, 58850 KiB  

Open AccessArticle

Development of Elastoplastic-Damage Model of AlFeSi Phase for Aluminum Alloy 6061

by Hailong Wang, Wenping Deng, Tao Zhang, Jianhua Yao and Sujuan Wang

Metals 2021, 11(6), 954; https://doi.org/10.3390/met11060954 - 12 Jun 2021

Cited by 3 | Viewed by 3297

Abstract

Material properties affect the surface finishing in ultra-precision diamond cutting (UPDC), especially for aluminum alloy 6061 (Al6061) in which the cutting-induced temperature rise generates different types of precipitates on the machined surface. The precipitates generation not only changes the material properties but also [...] Read more.

Material properties affect the surface finishing in ultra-precision diamond cutting (UPDC), especially for aluminum alloy 6061 (Al6061) in which the cutting-induced temperature rise generates different types of precipitates on the machined surface. The precipitates generation not only changes the material properties but also induces imperfections on the generated surface, therefore increasing surface roughness for Al6061 in UPDC. To investigate precipitate effect so as to make a more precise control for the surface quality of the diamond turned Al6061, it is necessary to confirm the compositions and material properties of the precipitates. Previous studies have indicated that the major precipitate that induces scratch marks on the diamond turned Al6061 is an AlFeSi phase with the composition of Al_86.1Fe_8.3Si_5.6. Therefore, in this paper, to study the material properties of the AlFeSi phase and its influences on ultra-precision machining of Al6061, an elastoplastic-damage model is proposed to build an elastoplastic constitutive model and a damage failure constitutive model of Al_86.1Fe_8.3Si_5.6. By integrating finite element (FE) simulation and JMatPro, an efficient method is proposed to confirm the physical and thermophysical properties, temperature-phase transition characteristics, as well as the stress–strain curves of Al_86.1Fe_8.3Si_5.6. Based on the developed elastoplastic-damage parameters of Al_86.1Fe_8.3Si_5.6, FE simulations of the scratch test for Al_86.1Fe_8.3Si_5.6 are conducted to verify the developed elastoplastic-damage model. Al_86.1Fe_8.3Si_5.6 is prepared and scratch test experiments are carried out to compare with the simulation results, which indicated that, the simulation results agree well with those from scratch tests and the deviation of the scratch force in X-axis direction is less than 6.5%. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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18 pages, 41138 KiB  

Open AccessArticle

WS-RCNN: Learning to Score Proposals for Weakly Supervised Instance Segmentation

by Jia-Rong Ou, Shu-Le Deng and Jin-Gang Yu

Sensors 2021, 21(10), 3475; https://doi.org/10.3390/s21103475 - 17 May 2021

Cited by 5 | Viewed by 2800

Abstract

Weakly supervised instance segmentation (WSIS) provides a promising way to address instance segmentation in the absence of sufficient labeled data for training. Previous attempts on WSIS usually follow a proposal-based paradigm, critical to which is the proposal scoring strategy. These works mostly rely [...] Read more.

Weakly supervised instance segmentation (WSIS) provides a promising way to address instance segmentation in the absence of sufficient labeled data for training. Previous attempts on WSIS usually follow a proposal-based paradigm, critical to which is the proposal scoring strategy. These works mostly rely on certain heuristic strategies for proposal scoring, which largely hampers the sustainable advances concerning WSIS. Towards this end, this paper introduces a novel framework for weakly supervised instance segmentation, called Weakly Supervised R-CNN (WS-RCNN). The basic idea is to deploy a deep network to learn to score proposals, under the special setting of weak supervision. To tackle the key issue of acquiring proposal-level pseudo labels for model training, we propose a so-called Attention-Guided Pseudo Labeling (AGPL) strategy, which leverages the local maximal (peaks) in image-level attention maps and the spatial relationship among peaks and proposals to infer pseudo labels. We also suggest a novel training loss, called Entropic OpenSet Loss, to handle background proposals more effectively so as to further improve the robustness. Comprehensive experiments on two standard benchmarking datasets demonstrate that the proposed WS-RCNN can outperform the state-of-the-art by a large margin, with an improvement of $11.6\%$ on PASCAL VOC 2012 and $10.7\%$ on MS COCO 2014 in terms of mAP${}_{50}$, which indicates that learning-based proposal scoring and the proposed WS-RCNN framework might be a promising way towards WSIS. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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11 pages, 3857 KiB  

Open AccessArticle

Analysis of Styrene-Butadiene Based Thermoplastic Magnetorheological Elastomers with Surface-Treated Iron Particles

by Arturo Tagliabue, Fernando Eblagon and Frank Clemens

Polymers 2021, 13(10), 1597; https://doi.org/10.3390/polym13101597 - 15 May 2021

Cited by 20 | Viewed by 2915

Abstract

Magnetorheological elastomers (MRE) are increasing in popularity in many applications because of their ability to change stiffness by applying a magnetic field. Instead of liquid-based 1 K and 2 K silicone, thermoplastic elastomers (TPE), based on styrene-butadiene-styrene block copolymers, have been investigated as [...] Read more.

Magnetorheological elastomers (MRE) are increasing in popularity in many applications because of their ability to change stiffness by applying a magnetic field. Instead of liquid-based 1 K and 2 K silicone, thermoplastic elastomers (TPE), based on styrene-butadiene-styrene block copolymers, have been investigated as matrix material. Three different carbonyl iron particles (CIPs) with different surface treatments were used as magneto active filler material. For the sample fabrication, the thermoplastic pressing method was used, and the MR effect under static and dynamic load was investigated. We show that for filler contents above 40 vol.-%, the linear relationship between powder content and the magnetorheological effect is no longer valid. We showed how the SiO₂ and phosphate coating of the CIPs affects the saturation magnetization and the shear modulus of MRE composites. A combined silica phosphate coating resulted in a higher shear modulus, and therefore, the MR effect decreased, while coating with SiO₂ only improved the MR effect. The highest performance was achieved at low deformations; a static MR effect of 73% and a dynamic MR effect of 126% were recorded. It was also shown that a lower melting viscosity of the TPE matrix helps to increase the static MR effect of anisotropic MREs, while low shear modulus is crucial for achieving high dynamic MR. The knowledge from TPE-based magnetic composites will open up new opportunities for processing such as injection molding, extrusion, and fused deposition modeling (FDM). Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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22 pages, 5629 KiB  

Open AccessArticle

Analysis of the Main Aspects Affecting Bonding in Stainless Steel Rebars Embedded in a Hydraulic Medium

by Fernando Ancio, Esperanza Rodriguez-Mayorga and Beatriz Hortigon

Metals 2021, 11(5), 786; https://doi.org/10.3390/met11050786 - 12 May 2021

Cited by 4 | Viewed by 2762

Abstract

The use of stainless steel rebars to reinforce masonry structures has become established as an eminently efficient methodology. From among the numerous techniques available, bed-joint structural repointing and superficial reinforcement with rebars or meshes attached to surfaces have become widespread, thanks to the [...] Read more.

The use of stainless steel rebars to reinforce masonry structures has become established as an eminently efficient methodology. From among the numerous techniques available, bed-joint structural repointing and superficial reinforcement with rebars or meshes attached to surfaces have become widespread, thanks to the excellent results they have produced in recent decades. Both techniques imply the use of diameters less than 6 mm and thin coverings. This article deals with the characterization of the bonding behavior of the rebar under these special circumstances. To this end, several finite element analyses have been carried out to identify the possible relationships between pull-out forces in various situations. These models allow certain conclusions to be drawn regarding the influence of the thickness of covering, boundary conditions, and geometrical aspects of the rebars in bonding. Certain mathematical expressions that relate the various conclusions from this research are finally laid out. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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19 pages, 1793 KiB  

Open AccessArticle

Instrumentalization of a Model for the Evaluation of the Level of Satisfaction of Graduates under an E-Learning Methodology: A Case Analysis Oriented to Postgraduate Studies in the Environmental Field

by Eduardo García Villena, Silvia Pueyo-Villa, Irene Delgado Noya, Kilian Tutusaus Pifarré, Roberto Ruíz Salces and Alina Pascual Barrera

Sustainability 2021, 13(9), 5112; https://doi.org/10.3390/su13095112 - 3 May 2021

Viewed by 2622

Abstract

The purpose of this article was to evaluate the level of satisfaction of a sample of graduates in relation to different online postgraduate programs in the environmental area, as part of the process of continuous improvement in which the educational institution was immersed [...] Read more.

The purpose of this article was to evaluate the level of satisfaction of a sample of graduates in relation to different online postgraduate programs in the environmental area, as part of the process of continuous improvement in which the educational institution was immersed for the renewal of its accreditation before the corresponding official bodies. Based on the bibliographic review of a series of models and tools, a Likert scale measurement instrument was developed. This instrument, once applied and validated, showed a good level of reliability, with more than three quarters of the participants having a positive evaluation of satisfaction. Likewise, to facilitate the relational study, and after confirming the suitability of performing a factor analysis, four variable grouping factors were determined, which explained a good part of the variability of the instrument’s items. As a result of the analysis, it was found that there were significant values of low satisfaction in graduates from the Eurasian area, mainly in terms of organizational issues and academic expectations. On the other hand, it was observed that the methodological aspects of the “Auditing” and “Biodiversity” programs showed higher levels of dissatisfaction than the rest, with no statistically significant relationships between gender, entry profile or age groups. The methodology followed and the rigor in determining the validity and reliability of the instrument, as well as the subsequent analysis of the results, endorsed by the review of the documented information, suggest that the instrument can be applied to other multidisciplinary programs for decision making with guarantees in the educational field. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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12 pages, 2799 KiB  

Open AccessCommunication

Incremental Learning in Modelling Process Analysis Technology (PAT)—An Important Tool in the Measuring and Control Circuit on the Way to the Smart Factory

by Shivani Choudhary, Deborah Herdt, Erik Spoor, José Fernando García Molina, Marcel Nachtmann and Matthias Rädle

Sensors 2021, 21(9), 3144; https://doi.org/10.3390/s21093144 - 1 May 2021

Cited by 1 | Viewed by 2893

Abstract

To meet the demands of the chemical and pharmaceutical process industry for a combination of high measurement accuracy, product selectivity, and low cost of ownership, the existing measurement and evaluation methods have to be further developed. This paper demonstrates the attempt to combine [...] Read more.

To meet the demands of the chemical and pharmaceutical process industry for a combination of high measurement accuracy, product selectivity, and low cost of ownership, the existing measurement and evaluation methods have to be further developed. This paper demonstrates the attempt to combine future Raman photometers with promising evaluation methods. As part of the investigations presented here, a new and easy-to-use evaluation method based on a self-learning algorithm is presented. This method can be applied to various measurement methods and is carried out here using an example of a Raman spectrometer system and an alcohol-water mixture as demonstration fluid. The spectra’s chosen bands can be later transformed to low priced and even more robust Raman photometers. The evaluation method gives more precise results than the evaluation through classical methods like one primarily used in the software package Unscrambler. This technique increases the accuracy of detection and proves the concept of Raman process monitoring for determining concentrations. In the example of alcohol/water, the computation time is less, and it can be applied to continuous column monitoring. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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29 pages, 15098 KiB  

Open AccessArticle

KEYme: Multifunctional Smart Toy for Children with Autism Spectrum Disorder

by Raquel Cañete, Sonia López and M. Estela Peralta

Sustainability 2021, 13(7), 4010; https://doi.org/10.3390/su13074010 - 3 Apr 2021

Cited by 9 | Viewed by 8405

Abstract

The role that design engineering plays in the quality of life and well-being of people with autism spectrum disorder around the world is extremely relevant; products are highly helpful when used as “intermediaries” in social interactions, as well as in the reinforcement of [...] Read more.

The role that design engineering plays in the quality of life and well-being of people with autism spectrum disorder around the world is extremely relevant; products are highly helpful when used as “intermediaries” in social interactions, as well as in the reinforcement of cognitive, motor and sensory skills. One of the most significant challenges engineers have to face lies in the complexity of defining those functional requirements of objects that will efficiently satisfy the specific needs of children with autism within a single product. Furthermore, despite the growing trends that point toward the integration of new technologies in the creation of toys for typically developing children, the variety of specialized smart products aimed at children with autism spectrum disorder is very limited. Based on this evidence the KEYme project was created, where a multifunctional smart toy is developed as a reinforcement system for multiple needs which is adaptable to different kinds of autism for therapies, educational centers or family environments. This approach involves the knowledge transfer from the latest neuroscience, medicine and psychology contributions to the engineering and industrial design field. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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17 pages, 6975 KiB  

Open AccessArticle

Experimental and Numerical Study on the Flexural Performance of Assembled Steel-Wood Composite Slab

by Guodong Li, Zhibin Liu, Wenjia Tang, Dongpo He and Wei Shan

Sustainability 2021, 13(7), 3814; https://doi.org/10.3390/su13073814 - 30 Mar 2021

Cited by 6 | Viewed by 2534

Abstract

This paper presents research on a new type of fabricated steel–wood composite floor material in the style of a slab-embedded beam flange, using test methods and finite element numerical analysis to study the flexural load-bearing performance of the composite slabs. Through experimental phenomena, [...] Read more.

This paper presents research on a new type of fabricated steel–wood composite floor material in the style of a slab-embedded beam flange, using test methods and finite element numerical analysis to study the flexural load-bearing performance of the composite slabs. Through experimental phenomena, the failure process and mechanism of the composite floor are analyzed, and the deformation performance and ultimate bearing capacity of the composite floor material are assessed. Through numerical analysis of the finite element model, the influence of the connection mode of the floor and the composite beam, the type and number of connectors, and the width of the flange of the composite beam on the bending performance of the composite beam–slab system is studied. The research results show that the fabricated steel–wood composite floor slab has good load-bearing and deformation performance. The self-tapping screw connection of the floor slab is better than the ordinary steel nail connection, and the reasonable screw spacing is 100–150 mm. Increasing the flange width of the composite beam can significantly improve the load-bearing capacity of the steel–wood composite floor component. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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12 pages, 7209 KiB  

Open AccessArticle

Assessment of Fennel Oil Microfluidized Nanoemulsions Stabilization by Advanced Performance Xanthan Gum

by Rubén Llinares, Pablo Ramírez, José Antonio Carmona, Luis Alfonso Trujillo-Cayado and José Muñoz

Foods 2021, 10(4), 693; https://doi.org/10.3390/foods10040693 - 24 Mar 2021

Cited by 14 | Viewed by 3089

Abstract

In this work, nanoemulsion-based delivery system was developed by encapsulation of fennel essential oil. A response surface methodology was used to study the influence of the processing conditions in order to obtain monomodal nanoemulsions of fennel essential oil using the microchannel homogenization technique. [...] Read more.

In this work, nanoemulsion-based delivery system was developed by encapsulation of fennel essential oil. A response surface methodology was used to study the influence of the processing conditions in order to obtain monomodal nanoemulsions of fennel essential oil using the microchannel homogenization technique. Results showed that it was possible to obtain nanoemulsions with very narrow monomodal distributions that were homogeneous over the whole observation period (three months) when the appropriate mechanical energy was supplied by microfluidization at 14 MPa and 12 passes. Once the optimal processing condition was established, nanoemulsions were formulated with advanced performance xanthan gum, which was used as both viscosity modifier and emulsion stabilizer. As a result, more desirable results with enhanced physical stability and rheological properties were obtained. From the study of mechanical spectra as a function of aging time, the stability of the nanoemulsions weak gels was confirmed. The mechanical spectra as a function of hydrocolloid concentration revealed that the rheological properties are marked by the biopolymer network and could be modulated depending on the amount of added gum. Therefore, this research supports the role of advanced performance xanthan gum as a stabilizer of microfluidized fennel oil-in-water nanoemulsions. In addition, the results of this research could be useful to design and formulate functional oil-in-water nanoemulsions with potential application in the food industry for the delivery of nutraceuticals and antimicrobials. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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15 pages, 2877 KiB  

Open AccessArticle

Total Saponins Isolated from Corni Fructus via Ultrasonic Microwave-Assisted Extraction Attenuate Diabetes in Mice

by Shujing An, Dou Niu, Ting Wang, Binkai Han, Changfen He, Xiaolin Yang, Haoqiang Sun, Ke Zhao, Jiefang Kang and Xiaochang Xue

Foods 2021, 10(3), 670; https://doi.org/10.3390/foods10030670 - 22 Mar 2021

Cited by 16 | Viewed by 4481

Abstract

Saponins have been extensively used in the food and pharmaceutical industries because of their potent bioactive and pharmacological functions including hypolipidemic, anti-inflammatory, expectorant, antiulcer and androgenic properties. A lot of saponins-containing foods are recommended as nutritional supplements for diabetic patients. As a medicine [...] Read more.

Saponins have been extensively used in the food and pharmaceutical industries because of their potent bioactive and pharmacological functions including hypolipidemic, anti-inflammatory, expectorant, antiulcer and androgenic properties. A lot of saponins-containing foods are recommended as nutritional supplements for diabetic patients. As a medicine and food homologous material, Corni Fructus (CF) contains various active ingredients and has the effect of treating diabetes. However, whether and how CF saponins attenuate diabetes is still largely unknown. Here, we isolated total saponins from CF (TSCF) using ultrasonic microwave-assisted extraction combined with response surface methodology. The extract was further purified by a nonpolar copolymer styrene type macroporous resin (HPD-300), with the yield of TSCF elevated to 13.96 mg/g compared to 10.87 mg/g obtained via unassisted extraction. When used to treat high-fat diet and streptozotocin-induced diabetic mice, TSCF significantly improved the glucose and lipid metabolisms of T2DM mice. Additionally, TSCF clearly ameliorated inflammation and oxidative stress as well as pancreas and liver damages in the diabetic mice. Mechanistically, TSCF potently regulated insulin receptor (INSR)-, glucose transporter 4 (GLUT4)-, phosphatidylinositol 3-kinase (PI3K)-, and protein kinase B (PKB/AKT)-associated signaling pathways. Thus, our data collectively demonstrated that TSCF could be a promising functional food ingredient for diabetes improvement. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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18 pages, 6875 KiB  

Open AccessFeature PaperArticle

Synergistic Effect of rhBMP-2 Protein and Nanotextured Titanium Alloy Surface to Improve Osteogenic Implant Properties

by Andrea Mesa-Restrepo, Ana Civantos, Jean Paul Allain, Edwin Patiño, Juan Fernando Alzate, Norman Balcázar, Robinson Montes, Juan José Pavón, José Antonio Rodríguez-Ortiz and Yadir Torres

Metals 2021, 11(3), 464; https://doi.org/10.3390/met11030464 - 11 Mar 2021

Cited by 7 | Viewed by 3000

Abstract

One of the major limitations during titanium (Ti) implant osseointegration is the poor cellular interactions at the biointerface. In the present study, the combined effect of recombinant human Bone Morphogenetic Protein-2 (rhBMP-2) and nanopatterned Ti6Al4V fabricated with Directed irradiation synthesis (DIS) is investigated [...] Read more.

One of the major limitations during titanium (Ti) implant osseointegration is the poor cellular interactions at the biointerface. In the present study, the combined effect of recombinant human Bone Morphogenetic Protein-2 (rhBMP-2) and nanopatterned Ti6Al4V fabricated with Directed irradiation synthesis (DIS) is investigated in vitro. This environmentally-friendly plasma uses ions to create self-organized nanostructures on the surfaces. Nanocones (≈36.7 nm in DIS 80°) and thinner nanowalls (≈16.5 nm in DIS 60°) were fabricated depending on DIS incidence angle and observed via scanning electron microscopy. All samples have a similar crystalline structure and wettability, except for sandblasted/acid-etched (SLA) and acid-etched/anodized (Anodized) samples which are more hydrophilic. Biological results revealed that the viability and adhesion properties (vinculin expression and cell spreading) of DIS 80° with BMP-2 were similar to those polished with BMP-2, yet we observed more filopodia on DIS 80° (≈39 filopodia/cell) compared to the other samples (<30 filopodia/cell). BMP-2 increased alkaline phosphatase activity in all samples, tending to be higher in DIS 80°. Moreover, in the mineralization studies, DIS 80° with BMP-2 and Anodized with BMP-2 increased the formation of calcium deposits (>3.3 fold) compared to polished with BMP-2. Hence, this study shows there is a synergistic effect of BMP-2 and DIS surface modification in improving Ti biological properties which could be applied to Ti bone implants to treat bone disease. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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17 pages, 4245 KiB  

Open AccessArticle

A Straightforward and Efficient Instance-Aware Curved Text Detector

by Fan Zhao, Sidi Shao, Lin Zhang and Zhiquan Wen

Sensors 2021, 21(6), 1945; https://doi.org/10.3390/s21061945 - 10 Mar 2021

Cited by 3 | Viewed by 3127

Abstract

A challenging aspect of scene text detection is to handle curved texts. In order to avoid the tedious manual annotations for training curve text detector, and to overcome the limitation of regression-based text detectors to irregular text, we introduce straightforward and efficient instance-aware [...] Read more.

A challenging aspect of scene text detection is to handle curved texts. In order to avoid the tedious manual annotations for training curve text detector, and to overcome the limitation of regression-based text detectors to irregular text, we introduce straightforward and efficient instance-aware curved scene text detector, namely, look more than twice (LOMT), which makes the regression-based text detection results gradually change from loosely bounded box to compact polygon. LOMT mainly composes of curve text shape approximation module and component merging network. The shape approximation module uses a particle swarm optimization-based text shape approximation method (called PSO-TSA) to fine-tune the quadrilateral text detection results to fit the curved text. The component merging network merges incomplete text sub-parts of text instances into more complete polygon through instance awareness, called ICMN. Experiments on five text datasets demonstrate that our method not only achieves excellent performance but also has relatively high speed. Ablation experiments show that PSO-TSA can solve the text’s shape optimization problem efficiently, and ICMN has a satisfactory merger effect. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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21 pages, 5296 KiB  

Open AccessArticle

AnkFall—Falls, Falling Risks and Daily-Life Activities Dataset with an Ankle-Placed Accelerometer and Training Using Recurrent Neural Networks

by Francisco Luna-Perejón, Luis Muñoz-Saavedra, Javier Civit-Masot, Anton Civit and Manuel Domínguez-Morales

Sensors 2021, 21(5), 1889; https://doi.org/10.3390/s21051889 - 8 Mar 2021

Cited by 22 | Viewed by 4084

Abstract

Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits do not prevent falls when the elderly person [...] Read more.

Falls are one of the leading causes of permanent injury and/or disability among the elderly. When these people live alone, it is convenient that a caregiver or family member visits them periodically. However, these visits do not prevent falls when the elderly person is alone. Furthermore, in exceptional circumstances, such as a pandemic, we must avoid unnecessary mobility. This is why remote monitoring systems are currently on the rise, and several commercial solutions can be found. However, current solutions use devices attached to the waist or wrist, causing discomfort in the people who wear them. The users also tend to forget to wear the devices carried in these positions. Therefore, in order to prevent these problems, the main objective of this work is designing and recollecting a new dataset about falls, falling risks and activities of daily living using an ankle-placed device obtaining a good balance between the different activity types. This dataset will be a useful tool for researchers who want to integrate the fall detector in the footwear. Thus, in this work we design the fall-detection device, study the suitable activities to be collected, collect the dataset from 21 users performing the studied activities and evaluate the quality of the collected dataset. As an additional and secondary study, we implement a simple Deep Learning classifier based on this data to prove the system’s feasibility. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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12 pages, 12231 KiB  

Open AccessArticle

Strengthening of Porcine Plasma Protein Superabsorbent Materials through a Solubilization-Freeze-Drying Process

by Estefanía Álvarez-Castillo, Carlos Bengoechea and Antonio Guerrero

Polymers 2021, 13(5), 772; https://doi.org/10.3390/polym13050772 - 3 Mar 2021

Cited by 4 | Viewed by 2398

Abstract

The replacement of common acrylic derivatives by biodegradable materials in the formulation of superabsorbent materials would lessen the associated environmental impact. Moreover, the use of by-products or biowastes from the food industry that are usually discarded would promote a desired circular economy. The [...] Read more.

The replacement of common acrylic derivatives by biodegradable materials in the formulation of superabsorbent materials would lessen the associated environmental impact. Moreover, the use of by-products or biowastes from the food industry that are usually discarded would promote a desired circular economy. The present study deals with the development of superabsorbent materials based on a by-product from the meat industry, namely plasma protein, focusing on the effects of a freeze-drying stage before blending with glycerol and eventual injection molding. More specifically, this freeze-drying stage is carried out either directly on the protein flour or after its solubilization in deionized water (10% w/w). Superabsorbent materials obtained after this solubilization-freeze-drying process display higher Young’s modulus and tensile strength values, without affecting their water uptake capacity. As greater water uptake is commonly related to poorer mechanical properties, the proposed solubilization-freeze-drying process is a useful strategy for producing strengthened hydrophilic materials. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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24 pages, 4657 KiB  

Open AccessArticle

Superficial Characteristics and Functionalization Effectiveness of Non-Toxic Glutathione-Capped Magnetic, Fluorescent, Metallic and Hybrid Nanoparticles for Biomedical Applications

by C. Fernández-Ponce, J. M. Mánuel, R. Fernández-Cisnal, E. Félix, J. Beato-López, J. P. Muñoz-Miranda, A. M. Beltrán, A. J. Santos, F. M. Morales, M. P. Yeste, O. Bomati-Miguel, R. Litrán and F. García-Cózar

Metals 2021, 11(3), 383; https://doi.org/10.3390/met11030383 - 26 Feb 2021

Cited by 8 | Viewed by 2986

Abstract

An optimal design of nanoparticles suitable for biomedical applications requires proper functionalization, a key step in the synthesis of such nanoparticles, not only for subsequent crosslinking to biological targets and to avoid cytotoxicity, but also to endow these materials with colloidal stability. In [...] Read more.

An optimal design of nanoparticles suitable for biomedical applications requires proper functionalization, a key step in the synthesis of such nanoparticles, not only for subsequent crosslinking to biological targets and to avoid cytotoxicity, but also to endow these materials with colloidal stability. In this sense, a reliable characterization of the effectiveness of the functionalization process would, therefore, be crucial for subsequent bioconjugations. In this work, we have analyzed glutathione as a means to functionalize four of the most widely used nanoparticles in biomedicine, one of which is a hybrid gold-magnetic-iron-oxide nanoparticle synthetized by a simple and novel method that we propose in this article. We have analyzed the colloidal characteristics that the glutathione capping provides to the different nanoparticles and, using information on the Z-potential, we have deduced the chemical group used by glutathione to link to the nanoparticle core. We have used electron microscopy for further structural and chemical characterization of the nanoparticles. Finally, we have evaluated nanoparticle cytotoxicity, studying cell viability after incubation with different concentrations of nanoparticles, showing their suitability for biomedical applications. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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18 pages, 3017 KiB  

Open AccessArticle

Instantaneous Disturbance Index for Power Distribution Networks

by María Dolores Borrás-Talavera, Juan Carlos Bravo and César Álvarez-Arroyo

Sensors 2021, 21(4), 1348; https://doi.org/10.3390/s21041348 - 14 Feb 2021

Cited by 2 | Viewed by 3157

Abstract

The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From [...] Read more.

The stability of power systems is very sensitive to voltage or current variations caused by the discontinuous supply of renewable power feeders. Moreover, the impact of these anomalies varies depending on the sensitivity/resilience of customer and transmission system equipment to those deviations. From any of these points of view, an instantaneous characterization of power quality (PQ) aspects becomes an important task. For this purpose, a wavelet-based power quality indices (PQIs) are introduced in this paper. An instantaneous disturbance index (ITD(t)) and a Global Disturbance Ratio index (GDR) are defined to integrally reflect the PQ level in Power Distribution Networks (PDN) under steady-state and/or transient conditions. With only these two indices it is possible to quantify the effects of non-stationary disturbances with high resolution and precision. These PQIs offer an advantage over other similar because of the suitable choice of mother wavelet function that permits to minimize leakage errors between wavelet levels. The wavelet-based algorithms which give rise to these PQIs can be implemented in smart sensors and used for monitoring purposes in PDN. The applicability of the proposed indices is validated by using a real-time experimental platform. In this emulated power system, signals are generated and real-time data are analyzed by a specifically designed software. The effectiveness of this method of detection and identification of disturbances has been proven by comparing the proposed PQIs with classical indices. The results confirm that the proposed method efficiently extracts the characteristics of each component from the multi-event test signals and thus clearly indicates the combined effect of these events through an accurate estimation of the PQIs. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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21 pages, 5402 KiB  

Open AccessArticle

OpenADR and Agreement Audit Architecture for a Complete Cycle of a Flexibility Solution

by Antonio Parejo, Sebastián García, Enrique Personal, Juan Ignacio Guerrero, Antonio García and Carlos Leon

Sensors 2021, 21(4), 1204; https://doi.org/10.3390/s21041204 - 9 Feb 2021

Cited by 5 | Viewed by 3703

Abstract

Nowadays, the presence of renewable generation systems and mobile loads (i.e., electric vehicle) spread throughout the distribution network is increasing. The problem is that this type of system introduces an added difficulty since they present a strong dependence on the meteorology and the [...] Read more.

Nowadays, the presence of renewable generation systems and mobile loads (i.e., electric vehicle) spread throughout the distribution network is increasing. The problem is that this type of system introduces an added difficulty since they present a strong dependence on the meteorology and the mobility needs of the users. This problem forces the distribution system operators to seek tools that make it possible to balance the relationship between consumption and generation. In this sense, automated demand response systems are an appropriate solution that allow the operator to request specific reductions in customers’ consumption, offering a discount to the customer and avoiding network congestion. This paper analyzes the implementation and architecture of a demand response solution based on OpenADR standard and its possible integration with a building management system through a use case. As will be analyzed, a key part of the architecture is the measurement system based on smart meters acting as sensors. This is the base of the auditing system which makes it possible to verify compliance with the consumption reduction agreements. Additionally, this study is completed with a parallel auditing system which makes it possible to verify compliance with the consumption reduction agreements. All of the proposed demand response cycle is implemented as a proof of concept in a classroom in the Escuela Politécnica Superior at the University of Seville, which makes it possible to identify the advantages of this architecture in the ambit of connection between distribution network and buildings. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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13 pages, 1755 KiB  

Open AccessArticle

Performance Evaluation of Deep Learning-Based Prostate Cancer Screening Methods in Histopathological Images: Measuring the Impact of the Model’s Complexity on Its Processing Speed

by Lourdes Duran-Lopez, Juan P. Dominguez-Morales, Antonio Rios-Navarro, Daniel Gutierrez-Galan, Angel Jimenez-Fernandez, Saturnino Vicente-Diaz and Alejandro Linares-Barranco

Sensors 2021, 21(4), 1122; https://doi.org/10.3390/s21041122 - 5 Feb 2021

Cited by 17 | Viewed by 3372

Abstract

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018. As it has been estimated, its mortality will double by 2040, mostly in countries with limited resources. These numbers [...] Read more.

Prostate cancer (PCa) is the second most frequently diagnosed cancer among men worldwide, with almost 1.3 million new cases and 360,000 deaths in 2018. As it has been estimated, its mortality will double by 2040, mostly in countries with limited resources. These numbers suggest that recent trends in deep learning-based computer-aided diagnosis could play an important role, serving as screening methods for PCa detection. These algorithms have already been used with histopathological images in many works, in which authors tend to focus on achieving high accuracy results for classifying between malignant and normal cases. These results are commonly obtained by training very deep and complex convolutional neural networks, which require high computing power and resources not only in this process, but also in the inference step. As the number of cases rises in regions with limited resources, reducing prediction time becomes more important. In this work, we measured the performance of current state-of-the-art models for PCa detection with a novel benchmark and compared the results with PROMETEO, a custom architecture that we proposed. The results of the comprehensive comparison show that using dedicated models for specific applications could be of great importance in the future. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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14 pages, 3752 KiB  

Open AccessArticle

Incorporation of ZnO Nanoparticles into Soy Protein-Based Bioplastics to Improve Their Functional Properties

by Mercedes Jiménez-Rosado, Víctor Perez-Puyana, Pablo Sánchez-Cid, Antonio Guerrero and Alberto Romero

Polymers 2021, 13(4), 486; https://doi.org/10.3390/polym13040486 - 4 Feb 2021

Cited by 29 | Viewed by 4385

Abstract

The union of nanoscience (nanofertilization) with controlled release bioplastic systems could be a key factor for the improvement of fertilization in horticulture, avoiding excessive contamination and reducing the price of the products found in the current market. In this context, the objective of [...] Read more.

The union of nanoscience (nanofertilization) with controlled release bioplastic systems could be a key factor for the improvement of fertilization in horticulture, avoiding excessive contamination and reducing the price of the products found in the current market. In this context, the objective of this work was to incorporate ZnO nanoparticles in soy protein-based bioplastic processed using injection moulding. Thus, the concentration of ZnO nanoparticles (0 wt%, 1.0 wt%, 2.0 wt%, 4.5 wt%) and mould temperature (70 °C, 90 °C and 110 °C) were evaluated through a mechanical (flexural and tensile properties), morphological (microstructure and nanoparticle distribution) and functional (water uptake capacity, micronutrient release and biodegradability) characterization. The results indicate that these parameters play an important role in the final characteristics of the bioplastics, being able to modify them. Ultimately, this study increases the versatility and functionality of the use of bioplastics and nanofertilization in horticulture, helping to prevent the greatest environmental impact caused. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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12 pages, 2740 KiB  

Open AccessEditor’s ChoiceArticle

Effects of Mould Temperature on Rice Bran-Based Bioplastics Obtained by Injection Moulding

by María Alonso-González, Manuel Felix, Antonio Guerrero and Alberto Romero

Polymers 2021, 13(3), 398; https://doi.org/10.3390/polym13030398 - 27 Jan 2021

Cited by 28 | Viewed by 4886

Abstract

The high production rate of conventional plastics and their low degradability result in severe environmental problems, such as plastic accumulation and some other related consequences. One alternative to these materials is the production of oil-free bioplastics, based on wastes from the agro-food industry, [...] Read more.

The high production rate of conventional plastics and their low degradability result in severe environmental problems, such as plastic accumulation and some other related consequences. One alternative to these materials is the production of oil-free bioplastics, based on wastes from the agro-food industry, which are biodegradable. Not only is rice bran an abundant and non-expensive waste, but it is also attractive due to its high protein and starch content, which can be used as macromolecules for bioplastic production. The objective of this work was to develop rice-bran-based bioplastics by injection moulding. For this purpose, this raw material was mixed with a plasticizer (glycerol), analysing the effect of three mould temperatures (100, 130 and 150 °C) on the mechanical and microstructural properties and water absorption capacity of the final matrices. The obtained results show that rice bran is a suitable raw material for the development of bioplastics whose properties are strongly influenced by the processing conditions. Thus, higher temperatures produce stiffer and more resistant materials (Young’s modulus improves from 12 ± 7 MPa to 23 ± 6 and 33 ± 6 MPa when the temperature increases from 100 to 130 and 150 °C, respectively); however, these materials are highly compact and, consequently, their water absorption capacity diminishes. On the other hand, although lower mould temperatures lead to materials with lower mechanical properties, they exhibit a less compact structure, resulting in enhanced water absorption capacity. Full article

(This article belongs to the Topic Scientific Advances in STEM: From Professor to Students)

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